{"uid":"cap_akqxxv2NskZLg_RRorRaA","slug":"kihustle-json-exponential-smoothing-2d93c124","name":"KiHustle JSON Exponential Smoothing","description":"Kostenlose Guides, Solo-Playbooks und Artikel zu KI, Automation und Side Hustles — für Menschen, die mit echten Systemen online Einkommen aufbauen wollen. Transparent finanziert über faire Affiliate-Links.","url":"https://kihustle.tech/agents/api/v1/json-exponential-smoothing","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"alpha":{"type":"number"},"values":{"type":"array","items":{"type":"number"}}}},"responseSchema":{"type":"json","example":{"result":"processed","status":"success"}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.002","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.002/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.002","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.002","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_N-QNa9Z-hCgDGwzakGokR","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.002","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Applies exponential smoothing to a numeric time series using a given alpha parameter and returns the smoothed values","exampleAgentPrompt":"Can you apply exponential smoothing with an alpha of 0.3 to this series of weekly sales figures: [120, 135, 128, 142, 155, 149, 160]?","exampleUseCases":[{"title":"Smooth noisy IoT sensor readings","prompt":"I have a stream of temperature sensor readings that are quite noisy — [22.1, 23.5, 21.8, 24.0, 22.7, 23.9, 21.5] — can you apply exponential smoothing with alpha 0.4 to get a cleaner trend?"},{"title":"Trend smoothing for financial data","prompt":"Take these monthly revenue figures [5000, 5300, 4800, 5600, 5200, 5900, 6100] and smooth them using exponential smoothing with alpha 0.2 so I can see the underlying trend more clearly."},{"title":"Preprocessing data for forecasting pipeline","prompt":"Before I run my forecast, can you exponentially smooth this sequence of daily visitor counts [210, 198, 225, 240, 215, 230, 245] using an alpha of 0.5?"}],"resultDescription":"Returns a JSON object with a 'result' field containing the processed smoothed series and a 'status' field indicating success. The smoothed output corresponds element-wise to the input array, with noise reduced according to the alpha weighting factor.","failureModes":["Missing or invalid alpha value (not a number between 0 and 1) may cause processing errors","Empty or non-numeric values array may result in a failed response","Alpha outside [0,1] range may produce unexpected smoothing behavior","Malformed JSON body returns an error response","Very large arrays may cause timeout or processing issues"],"whenToPreferThis":"Choose this endpoint when you need a lightweight, pay-per-call exponential smoothing computation without setting up a full data science environment. Ideal for preprocessing noisy numeric sequences before forecasting, visualizing trends, or feeding into downstream ML pipelines. Best suited for moderate-length numeric arrays where a simple, configurable alpha-based smoothing pass is sufficient.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-13T19:02:59.371Z","isFirstParty":false}